There are two new items (2007-Nov-15) that might be of interest to
colleagues working in EEG/MEG tomography and brain connectivity.
1. A technical report with new measures of connectivity:
“Instantaneous and lagged measurements of linear and nonlinear dependence
between groups of multivariate time series: frequency decomposition”
can be downloaded from:
http://arxiv.org/abs/0711.1455
The abstract can be found below.
2. The new sLORETA/eLORETA software package (2007-Nov-15) is now
available. It includes:
2.a. The new eLORETA method
2.b. Tools for defining cortical regions of interest (ROIs)
2.c. New instantaneous and lagged measurements of linear and nonlinear
dependence between groups of multivariate time series. Connectivity is
computed between cortical regions of interest (ROIs)
2.d. Statistical tools (SnPM methodology) for hypothesis testing on the
new connectivity measures.
Download URL and password for installation remain the same, and can be
obtained (if you write your email address correctly) at:
http://www.uzh.ch/keyinst/NewLORETA/PassWord/PassWordSloreta.htm
Presently, the software runs on Windows. Hopefully, it can all be re-
implemented soon in JAVA, which would make it platform independent (and
open source).
Cordially,
Roberto
--
R.D. Pascual-Marqui
The KEY Institute for Brain-Mind Research
University Hospital of Psychiatry
pascualm at key.uzh.ch
www.keyinst.uzh.ch/loreta
-----------------------------------------------------
Abstract: Measures of linear dependence (coherence) and nonlinear
dependence (phase synchronization) between any number of multivariate time
series are defined. The measures are expressed as the sum of lagged
dependence and instantaneous dependence. The measures are non-negative,
and take the value zero only when there is independence of the pertinent
type. These measures are defined in the frequency domain and are
applicable to stationary and non-stationary time series. These new results
extend and refine significantly those presented in a previous technical
report (Pascual-Marqui 2007, arXiv:0706.1776 [stat.ME],
http://arxiv.org/abs/0706.1776 ), and have been largely motivated by the
seminal paper on linear feedback by Geweke (1982 JASA 77:304-313). One
important field of application is neurophysiology, where the time series
consist of electric neuronal activity at several brain locations.
Coherence and phase synchronization are interpreted as “connectivity”
between locations. However, any measure of dependence is highly
contaminated with an instantaneous, non-physiological contribution due to
volume conduction and low spatial resolution. The new techniques remove
this confounding factor considerably. Moreover, the measures of dependence
can be applied to any number of brain areas jointly, i.e. distributed
cortical networks, whose activity can be estimated with eLORETA (Pascual-
Marqui 2007, arXiv:0710.3341 [math-ph], http://arxiv.org/abs/0710.3341 ).
|